CN108001261A - Power battery charged state computational methods and monitoring device based on fuzzy algorithmic approach - Google Patents

Abstract

The invention discloses a method and device for calculating the state of charge of a power battery based on a fuzzy algorithm. The method includes the following steps: 1) selecting input and output variables; 2) defining input and output membership functions; 3) establishing fuzzy control rules ; 4) Fuzzy reasoning; 5) Defuzzification; The battery charge state monitoring device based on the fuzzy algorithm includes a microprocessor and a data acquisition module and a liquid crystal display module respectively connected to the microprocessor. The data acquisition module can collect power The voltage, current, temperature and resistance of the battery are transmitted to the microprocessor, including the host computer, which is connected to the microprocessor and can realize data transmission. The host computer can use the battery state of charge calculation method based on fuzzy algorithm Get the battery SOC value. The present invention has the following advantages and effects: the monitoring device can detect the voltage, current, resistance and temperature values of the battery, and calculate the SOC value of the battery through the calculation method of the state of charge of the power battery based on the fuzzy algorithm.

Description

Calculation method and monitoring device for power battery state of charge based on fuzzy algorithm

technical field

The invention relates to the field of electric vehicle power battery management systems, in particular to a fuzzy algorithm-based calculation method and a monitoring device for the state of charge of a power battery.

Background technique

With the increasingly serious environmental pollution and energy crisis, new energy vehicles have become an important direction of the future automotive industry. Accurate battery status has become an important factor in promoting the development of electric vehicles. The accuracy of the battery will not only affect the itinerary planned by the user, but also affect the mileage and service life of the battery. At present, under the strong advocacy of the country, electric vehicles have become a convenient means of transportation that Chinese residents are willing to try.

There are several methods for estimating the current battery state of charge (battery SOC value) as follows: (1) Current integration method, which is better when the initial state of the battery is known, the current acquisition accuracy is high, and the duration is not too long. estimated accuracy. However, it is difficult to know the initial state of the battery in normal use, and the acquisition accuracy is low. (2) The open circuit voltage method, this method is limited to the use of the battery in the open circuit state, and because the power battery has capacitive properties, the battery must be left for a long time after the open circuit to return to the true open circuit voltage potential, so it is difficult accomplish. (3) Kalman filter method, this method has a strong dependence on the battery model, to ensure the estimation accuracy requires accurate battery model parameters, it is difficult to obtain parameters for power batteries.

Contents of the invention

The object of the present invention is to provide a method for calculating the state of charge of a power battery based on a fuzzy algorithm, which can calculate an accurate battery SOC value by inputting voltage, current, resistance and temperature values and using the algorithm.

The above-mentioned technical purpose of the present invention is achieved through the following technical solutions: a method for calculating the state of charge of a battery based on a fuzzy algorithm, including the following steps: 1) Select input and output variables, and select voltage, current, temperature and resistance values as Input signal, select the battery SOC value as the output signal; 2) Define the input and output membership functions, set the voltage measurement value to e1 and divide e1 into nine fuzzy states, set the current measurement value to e2 and divide e2 into Six fuzzy states, set resistance measurement value to e3 and divide e3 into three fuzzy states, set temperature measurement value to e4 and divide e4 into five fuzzy states, set battery SOC value to u and divide u into For the five fuzzy states, establish membership functions for all the above-mentioned fuzzy states; 3) Establish fuzzy control rules, and formulate corresponding fuzzy control rules for the fuzzy states of the current measured values e1, e2, e3 and e4 based on a large number of actual measurement data; 4) Perform fuzzy reasoning, and obtain the fuzzy state of the battery SOC value u through fuzzy control rules; 5) Defuzzify, use the weighted average method to defuzzify, and obtain an accurate battery SOC value.

By adopting the above-mentioned technical scheme, the voltage, current, temperature and internal resistance of the battery are used as fuzzy control inputs, especially the internal resistance is selected as the input, and the prediction result is more accurate. Because of the aging of the battery, the change of temperature, the internal resistance of the battery will change accordingly, and these factors will affect the estimation of the state of charge of the battery, so the change of internal resistance has a great impact on the prediction of SOC, and the internal resistance of the battery Taking this factor into account, the prediction results obtained will be more accurate. The fuzzy control algorithm is a fuzzy control rule that has been established through a large number of experimental data, and has obtained better performance results.

Another object of the present invention is to provide a battery charge state monitoring device based on a fuzzy algorithm, which can detect the voltage, current, resistance and temperature of the battery and transmit the data to the host computer for processing through communication. The device is also connected with a display and can display the voltage, current, temperature, resistance internal resistance, running time, battery SOC value and fault code information of the power battery.

The above technical purpose of the present invention is achieved through the following technical solutions: a battery state of charge monitoring device based on fuzzy algorithm, including a microprocessor and a data acquisition module and a liquid crystal display module connected to the microprocessor respectively, said The data acquisition module can collect the voltage, current, temperature and resistance value of the power battery and transmit them to the microprocessor, and also includes a host computer, which is connected to the microprocessor and can realize data transmission. The method for calculating the state of charge of the battery based on the fuzzy algorithm described in 1 obtains the SOC value of the battery.

By adopting the above technical solution, the data acquisition module can collect the voltage, current, temperature and resistance value of the power battery and transmit it to the microprocessor. The microprocessor is connected to the host computer and transmits the data to the host computer. Four parameters of current, temperature and internal resistance are processed.

It is further set as: the data acquisition module is connected to a trigger switch, the control terminal of the trigger switch is connected to the microprocessor, and the microprocessor can control the start-stop state of the data acquisition module through the control terminal of the trigger switch.

By adopting the above technical solution, when data abnormality occurs or the data acquisition module breaks down, the trigger switch can be used to close the data acquisition module so as to stop data acquisition.

It is further set as: the data acquisition module includes a voltage detection unit, a current detection unit, a temperature detection unit, a resistance detection unit and a timer and is respectively connected with the microprocessor and can realize data transmission, the voltage detection unit, the current detection unit The unit, the temperature detection unit and the resistance detection unit are all equipped with an AD conversion unit and realize AD conversion through the AD conversion unit, and the timer is used to calculate the running time of the power battery.

By adopting the above technical scheme, corresponding data can be collected, wherein the voltage value of the power battery is collected through the voltage detection unit and converted into a corresponding digital signal through the AD conversion unit; the current value of the power battery is collected through the current detection unit and passed through The AD conversion unit converts it into a corresponding digital signal; the temperature value of the power battery is collected by the temperature detection unit and converted into a corresponding digital signal by the AD conversion unit; the internal resistance value of the power battery is collected by the internal resistance detection unit and converted by AD units into corresponding digital signals.

It is further set as: both the host computer and the liquid crystal display module have a communication interface capable of communicating with the microprocessor, and the liquid crystal display module can display the voltage, current, temperature, internal resistance of the resistance, running time, charge SOC of the power battery value and fault code information.

By adopting the above technical solution, the microprocessor communicates with the upper computer and the liquid crystal display module respectively through the communication interface, so as to realize data transmission. The liquid crystal display module can display the temperature, current, voltage, internal resistance and battery SOC value of the power battery, so that users can understand the usage status of the power battery of electric vehicles and the cruising range of the power battery. When the power battery is overcharged, overdischarged, or the surface temperature of the power battery is too high, the liquid crystal display module can display the abnormal state of the battery to remind the user to stop for inspection or maintenance.

Description of drawings

Fig. 1 is the structural block diagram of embodiment;

Fig. 2 is the flowchart of fuzzy algorithm in the embodiment;

Fig. 3 is the graph of three kinds of membership functions in the embodiment;

Fig. 4 is fuzzy control rule 1 in the embodiment;

Fig. 5 is fuzzy control rule 2 in the embodiment;

Fig. 6 is the fuzzy control rule 3 in the embodiment.

In the figure: 1. Power battery; 2. Data acquisition module; 3. Voltage detection unit; 4. Current detection unit; 5. Temperature detection unit; 6. Resistance detection unit; 7. Timer; 8. Microprocessor; 9 , Liquid crystal display module; 10, PC.

Detailed ways

The present invention will be described in further detail below in conjunction with the accompanying drawings.

Referring to Fig. 1 , a fuzzy control-based power battery 1 state-of-charge monitoring device includes a data acquisition module 2, which is connected to a microprocessor 8 and can transmit the collected data to the microprocessor 8, and a host computer 10 Both the liquid crystal display module 9 and the liquid crystal display module 9 have a communication interface and realize data transmission with the microprocessor 8 through the communication interface.

Wherein, the data acquisition module 2 includes a voltage detection unit 3, a current detection unit 4, a temperature detection unit 5, a resistance detection unit 6 and a timer 7 and is respectively connected with a microprocessor 8 and can realize data transmission, the voltage The detection unit 3 , the current detection unit 4 , the temperature detection unit 5 and the resistance detection unit 6 are all equipped with an AD conversion unit and realize AD conversion through the AD conversion unit. The timer 7 is used to calculate the running time of the power battery 1 . The data acquisition module 2 is also connected with a trigger switch, the control terminal of the trigger switch is connected with the microprocessor 8, and the start-stop state of the data acquisition module 2 is controlled by receiving the signal sent by the microprocessor 8 . When abnormal data occurs or the data acquisition module 2 breaks down, the trigger switch can be used to close the data acquisition module 2 so as to stop data acquisition.

The voltage detection unit 3 includes a voltage sensor, the voltage sensor is connected between the positive and negative busbars of the power battery 1 in parallel, the output terminal of the voltage sensor is connected with the AD conversion unit, and the AD conversion unit can convert the analog signal of the detected voltage value into corresponding digital signals. The current detection unit 4 includes a current sensor, the current sensor is connected in series to the positive busbar of the power battery 1, the output end of the current sensor is connected with the AD conversion unit, and the AD conversion unit can convert the analog signal of the detected current value into a corresponding Digital signal. The temperature detection unit 5 includes a temperature sensor, the temperature sensor is attached to the surface of the power battery 1, the output end of the temperature sensor is connected with the AD conversion unit, and the AD conversion unit can convert the analog signal of the detected temperature value into a corresponding digital signal. The internal resistance detection unit includes an internal resistance measuring instrument, which is connected in series to the positive and negative busbars of the power battery 1, and the output terminal of the internal resistance measuring instrument is connected to the AD conversion unit, and the AD conversion module unit can convert the detected The analog signal of the resistance value is converted into a corresponding digital signal. The digital signals of voltage, current, temperature and resistance after AD conversion are all transmitted to the microprocessor 8 .

After the microprocessor 8 receives the digital signal for processing, it transmits it to the upper computer 10 through the communication interface. The communication method here adopts the I2C bus for communication. The I2C bus has a high penetration rate on the chip and the hardware structure is simple. After receiving the signal, the upper computer 10 calculates the state of charge of the battery according to the fuzzy control algorithm. Since the state of charge of the battery cannot be directly measured, the state of charge of the battery can only be estimated by measuring other parameters of the battery. Therefore, the choice of parameters is particularly important to estimate the state of charge of the battery using the fuzzy control algorithm. Among them, the voltage, current, temperature and internal resistance of the battery are highly correlated with the state of charge of the battery, so collecting the above data can make the estimation accuracy of the fuzzy control algorithm higher. After estimating the accurate battery SOC value, use the communication interface to transmit the data to the microprocessor 8. The microprocessor 8 is connected to the liquid crystal display module 9 and transmits the data to the liquid crystal display module 9 through the communication interface. The communication here also uses I2C bus for communication. The liquid crystal display module 9 can display the battery SOC value of the power battery 1 through the liquid crystal display inside it, and can also display the temperature, current, voltage and internal resistance of the power battery 1, for the user to understand the use of the power battery 1 of the electric vehicle condition and the cruising range of the power battery 1. When the power battery 1 is overcharged, overdischarged, or the surface temperature of the power battery 1 is too high, the liquid crystal display module 9 can display the abnormal state of the battery to remind the user to stop for inspection or maintenance.

Referring to Figure 2, the steps of the fuzzy control algorithm are:

1. Select input variable and output variable

Selecting suitable input variables and output variables is the first step of fuzzy control algorithm. Since the selection of input variables and output variables has a great influence on the results of the fuzzy control algorithm, it must be considered very carefully. The invention selects the voltage, current, temperature and resistance value of the battery as input variables, especially selects the internal resistance as the input, and the prediction result is more accurate. Because of the aging of the battery, the change of temperature, the internal resistance of the battery will change accordingly, and these factors will affect the estimation of the state of charge of the battery, so the change of internal resistance has a great impact on the prediction of SOC. At the same time, the battery SOC value is used as an output variable.

2. Define the input and output membership function

Referring to Figure 3, for the membership function, the more shaken the shape of the membership function, the higher the resolution and the higher the output sensitivity; the slower the change of the membership function, the lower the sensitivity. The present invention selects three most suitable membership functions according to a large amount of actual test data, including:

The triangle membership function (trimf), the expression is: y=trimf(x[a b c]), where the parameter x represents the scope of the variable universe, the parameters a and c correspond to the left and right vertices of the lower part of the triangle, and the parameter b corresponds to the upper part of the triangle vertex;

S-type membership function (smf), the expression is y=smf(x, [a b]), where x represents the scope of the variable domain, and the curve is a smooth spline curve between (a, b), and the left side of a The segment is 0, the right end of b is 1, and the jump point is (a+b)/2.

Z-type membership function (zmf), the expression is y=zmf(x, [a b]), where x represents the scope of the variable discourse, and the curve is a smooth spline curve between (a, b), on the left of a The segment is 1, the right end of b is 0, and the jump point is (a+b)/2.

First, fuzzy sets are specified for the input variables. According to the measured value e1 of the current voltage. Divide e1 into nine fuzzy states, namely very low (VVVL), very low (VVL), very low (VL), low (L), centered (MID), high (H), very high (VH), very high (VVH), very high (VVVH). Secondly, select the appropriate voltage range and establish the membership function of each fuzzy state accordingly, where the range of discourse is expressed as Range, specifically:

Range=[10 12.5];

MF1='VVVL':'zmf',[10.3 10.6];

MF2='VVL':'trimf',[10.2 10.6 11];

MF3='VL':'trimf',[10.65 11 11.2];

MF4='L':'trimf',[11 11.2 11.4];

MF5='MID':'trimf',[11.2 11.4 11.6];

MF6='H':'trimf',[11.4 11.6 11.8];

MF7='VH':'trimf',[11.6 11.8 12];

MF8='VVH':'trimf',[11.8 12 12.2];

MF9='VVVH':'smf',[12.05 12.3].

According to the measured value e2 of the current current. Divide e2 into six fuzzy states, namely very low (VVL), very low (VL), low (L), centered (MID), high (H), and very high (VH). Secondly, select the appropriate current range and establish the membership function of each fuzzy state accordingly, specifically:

Range=[0 100];

MF1='VVL':'zmf',[6 11];

MF2='VL':'trimf',[8 18 27.4];

MF3='L':'trimf',[11.8 27.4 40];

MF4='MID':'trimf',[27.4 42 60];

MF5='H':'trimf',[42.7 60 77.9];

MF6='VH':'smf',[60 77.9].

According to the measured value e3 of the current resistance. Divide e3 into three fuzzy states, namely low (L), center (MID), high (H). Secondly, select the appropriate current range and establish the membership function of each fuzzy state accordingly, specifically:

Range = [20 38];

MF1='L':'zmf',[20.72 26.48];

MF2='MID':'trimf',[24 26 30];

MF3='H':'smf',[28 38].

According to the measured value e4 of the current temperature. Divide e4 into five fuzzy states, namely low (L), very high (VH), very low (VL), centered (MID), high (H). Secondly, select the appropriate temperature range and establish the membership function of each fuzzy state accordingly, specifically:

Range=[-40 75];

MF1='L':'trimf',[-30 -15 10];

MF2='VH':'smf',[50 70.4];

MF3='VL':'zmf',[-37.13 -14.13];

MF4='MID':'trimf',[0 20 38];

MF5='H':'trimf',[30 40 55].

According to the current battery SOC value u. Divide u into seven fuzzy states, namely warning (ALARM), very low (VL), low (L), center (MID), high (H), very high (VH), full (FULL), and then select the appropriate temperature range and correspondingly establish the membership function of each fuzzy state, specifically:

Range=[0 1];

MF1='ALARM':'trimf',[0 0 0.15];

MF2='VL':'trimf',[0 0.15 0.31];

MF3='L':'trimf',[0.15 0.31 0.49];

MF4='MID':'trimf',[0.31 0.49 0.68];

MF5='H':'trimf',[0.49 0.66 0.81];

MF6='VH':'trimf',[0.68 0.86 1];

MF7='FULL':'trimf',[0.885 1 1].

3. Establish fuzzy control rules

Referring to Figure 4, Figure 5 and Figure 6, it is based on a large amount of experimental data, and the corresponding improvement methods obtained from experience in the actual measurement process are summarized into one-by-one control, specifically the tables in Figure 4, Figure 5 and Figure 6. For example, 1 1 0 0, 1 (1) : 1 in the first row and first column in Figure 4, the first number 1 from left to right indicates the fuzzy state of the voltage measurement value e1, and the second number 1 indicates the current measurement The fuzzy state of the value e2, the third number 0 represents the fuzzy state of the resistance measurement value e3, the fourth number 0 represents the fuzzy state of the temperature measurement value e4, the fifth number 1 represents the corresponding battery SOC value u, the sixth The number 1, that is, the 1 in the brackets indicates the weight, and the seventh number 1 indicates that the relationship between the input quantities is "and", that is, the fuzzy state of the four inputs must be satisfied at the same time to obtain the fuzzy state of the corresponding output.

4. Perform fuzzy reasoning

Carry out fuzzy reasoning according to the sentence "if A and B and C and D, then E", and also illustrate with 1 1 0 0, 1 (1) : 1 in the first row and first column of the table in Figure 4, when the input When the fuzzy state of the voltage measurement value e1 is 1, the fuzzy state of the current measurement value e2 is 2, the fuzzy state of the resistance measurement value e3 is 0, and the fuzzy state of the temperature measurement value e4 is 0, the output battery SOC value u can be obtained as 1. Based on the established fuzzy rules, different input fuzzy state groups can obtain the fuzzy state of the corresponding output u through fuzzy reasoning. The fuzzy state of the battery SOC value u is not accurate, and the result needs to be defuzzified to make the result more accurate.

5. Deblurring

There are many ways to defuzzify. Here, the weighted average method is chosen. The formula is (k1*a1+k2*a2+k3*a3+....+kn*an)/(k1+k2+k3+...+kn ), where (a1, a2, a3,....an) represent multiple battery SOC values, and the coefficients (k1, k2, k3,....kn) are weighted, indicating that the data behind this coefficient, in the entire percentage of statistics. Therefore, the weighted average method can be used to obtain accurate battery SOC according to the different proportions.

This specific embodiment is only an explanation of the present invention, and it is not a limitation of the present invention. Those skilled in the art can make modifications to this embodiment without creative contribution as required after reading this specification, but as long as they are within the rights of the present invention All claims are protected by patent law.

Claims (5)

1. A battery state of charge calculation method based on fuzzy algorithm, is characterized in that, comprises the steps: 1) Select the input and output variables, select voltage, current, temperature and resistance as the input signal, and select the battery SOC value as the output signal; 2) Define the input and output membership functions, set the voltage measurement value to e1 and divide e1 into nine fuzzy states, set the current measurement value to e2 and divide e2 into six fuzzy states, and set the resistance measurement value to e3 and divide e3 into three fuzzy states, set the temperature measurement value to e4 and divide e4 into five fuzzy states, set the battery SOC value to u and divide u into five fuzzy states, for all the above fuzzy states Establish membership function respectively; 3) Establish fuzzy control rules, and formulate corresponding fuzzy control rules for the fuzzy states of the current measured values e1, e2, e3, and e4 based on a large number of actual measurement data; 4) Carry out fuzzy reasoning, and obtain the fuzzy state of the battery SOC value u through fuzzy control rules; 5) Defuzzification, use the weighted average method to defuzzify, and get the accurate battery SOC value. 2. A battery charge state monitoring device based on a fuzzy algorithm, comprising a microprocessor (8) and a data acquisition module (2) and a liquid crystal display module (9) connected to the microprocessor (8) respectively, the data The acquisition module (2) can collect the voltage, current, temperature and resistance value of the power battery (1) and transmit it to the microprocessor (8), and is characterized in that: it also includes a host computer (10), and the host computer (10) It is connected with the microprocessor and can realize data transmission, and the host computer (10) can obtain the SOC value of the battery by using the method for calculating the state of charge of the battery based on the fuzzy algorithm described in claim 1. 3. The battery state of charge monitoring device based on fuzzy algorithm according to claim 2, characterized in that: the data acquisition module (2) is connected to a trigger switch, and the control terminal of the trigger switch is connected to the microprocessor (8) connected, the micro-processing (8) can control the start-stop state of the data acquisition module (2) through the control terminal of the trigger switch. 4. The battery state-of-charge monitoring device based on fuzzy algorithm according to claim 3, characterized in that: the data acquisition module (2) includes a voltage detection unit (3), a current detection unit (4), a temperature detection unit (5), resistance detection unit (6) and timer (7) are connected with microprocessor (8) respectively and can realize the transmission of data, described voltage detection unit (3), current detection unit (4), temperature Both the detection unit (5) and the resistance detection unit (6) are provided with an AD conversion unit and realize AD conversion through the AD conversion unit, and the timer (7) is used for calculating the running time of the power battery (1). 5. The battery state-of-charge monitoring device based on fuzzy algorithm according to claim 2, characterized in that: said host computer (10) and liquid crystal display module (9) all have the ability to communicate with the microprocessor (8). The communication interface of the liquid crystal display module (9) can display the voltage, current, temperature, resistance internal resistance, running time, battery SOC value and fault code information of the power battery (1).